Melbourne AI Security & Governance Summit 2027

Beat the rush and join us early for complimentary barista-made coffee and breakfast.

AI has moved into production faster than security and governance can keep up. This keynote frames the day's core risks and what secure-by-design AI actually requires.

• Why AI trust and resilience are now board-level priorities.
• Four forces reshaping AI risk: attackers, regulators, shadow adoption, agentic autonomy.
• What secure-by-design looks like for production AI.

APRA and ASIC have sharpened supervisory expectations, and Australia's National AI Plan is taking shape without a standalone AI Act. This session covers what's actually required now.

• What APRA and ASIC's supervisory letters require.
• How voluntary standards under the National AI Plan are likely to harden.
• Building a governance framework that can flex as rules change.

AI is changing the speed and scale of cybercrime. Threat actors are using generative AI to create more convincing phishing campaigns, develop malicious code, automate attacks, and identify vulnerabilities faster than ever.

This panel will explore how AI is reshaping the threat landscape, what security teams are seeing in the real world, and whether defensive AI can keep pace with increasingly sophisticated attackers.

• How AI is accelerating attacks and shortening the time organisations have to respond.
• Real-world examples of AI-powered phishing, malware, and automated cyberattacks.
• Where defensive AI can keep pace with attackers and where human expertise is still essential.

Moving an AI model from pilot to production introduces new security challenges. Controls that worked during testing may not be enough once the model is handling real data, users, and business processes.

This case study explores how one team secured a live AI model without slowing down adoption or undermining the business value of AI.

• What security gaps emerged when the AI model moved from pilot to production.
• How the team approached access controls, logging, and continuous monitoring.
• The incident response playbook they developed to identify, contain, and respond to AI-related threats.

A hands-on, interactive session working through a real AI security and governance scenario as a room. Details announced soon.

As employees adopt AI tools faster than organisations can govern them, security teams are facing growing risks around sensitive data, third-party platforms, and unsanctioned AI use.

This case study explores how one organisation gained visibility over its AI usage and introduced a practical approach to managing risk without blocking innovation.

• How the organisation uncovered the scale of unsanctioned AI tools being used across the business.
• How they assessed and risk-tiered AI tools and vendors rather than introducing a blanket ban.
• How they created a clear pathway to approved AI tools that employees would actually use.

As AI agents gain greater autonomy and access to business systems, prompt injection and unexpected agent behaviour can create serious security risks.

This case study examines a real prompt injection incident involving a production AI agent, how the attack unfolded, and the security measures introduced to reduce the risk of it happening again.

• How the prompt injection attack worked and where existing security controls failed.
• Why prompt injection remains difficult to prevent with a single, permanent solution.
• How guardrails, sandboxing, and human oversight were introduced to make AI agents safer.

As AI becomes embedded in critical business systems, attackers are finding new ways to target the models and data behind them. From manipulating training data to creating convincing deepfakes, these threats are creating a new set of challenges for security teams.

This panel explores how these attacks work, what organisations are seeing in practice, and the steps security teams can take to strengthen AI systems without needing specialist research capabilities.

• How adversarial attacks and model poisoning work, and how they differ from prompt injection.
• How organisations are detecting and responding to deepfakes in real-world environments.
• Practical ways to strengthen AI models and data against emerging attacks.

Small-group, discussion-based sessions where you'll work through real AI security and governance challenges with peers in similar roles. Roundtable topics will be announced soon.

Put your knowledge to the test in this fast-paced quiz covering real-world trivia, key concepts, and emerging trends. Compete for bragging rights — and a voucher — as the top scorer takes the crown.

As AI agents become more common across the business, they can quietly gain access to sensitive systems, data, and applications without the same oversight as human users.

This case study explores how one organisation identified the access its AI agents had accumulated and introduced stronger governance to manage non-human identities and reduce security risk.

• How the organisation discovered what systems and data its AI agents could access.
• How they applied least-privilege principles to autonomous, non-human identities.
• How they built ongoing visibility and controls as new AI agents were introduced.

As AI becomes more widely used across organisations, boards are under growing pressure to understand and oversee the risks that come with it. The challenge is giving leaders the right level of insight without overwhelming them with technical detail.

This keynote explores how organisations can communicate AI risk clearly, establish accountability, and give boards the knowledge they need to make informed decisions.

• What effective AI risk reporting looks like at board and executive level.
• How to establish clear ownership and accountability for AI-related risks.
• How to build AI literacy at board level without getting lost in technical detail.

Where are organisations most exposed when it comes to AI? This interactive think tank will use live audience voting to uncover the biggest AI security and governance challenges organisations are facing today.

Compare your organisation's approach with peers, identify common gaps, and explore where security teams should be focusing their attention and investment.

1. What is your biggest AI security blind spot: shadow AI, agentic access, model attacks, or third-party tools?
2. Who is responsible for AI risk in your organisation?
3. Have you experienced a prompt injection or AI agent incident, even a near-miss?
4. Is your board asking the right questions about AI risk?
5. Where should your next AI security investment be focused?

Unwind with your peers for a couple of drinks on us!

Beat the rush and join us early for complimentary barista-made coffee and breakfast.

AI has moved into production faster than security and governance can keep up. This keynote frames the day's core risks and what secure-by-design AI actually requires.

• Why AI trust and resilience are now board-level priorities.
• Four forces reshaping AI risk: attackers, regulators, shadow adoption, agentic autonomy.
• What secure-by-design looks like for production AI.

APRA and ASIC have sharpened supervisory expectations, and Australia's National AI Plan is taking shape without a standalone AI Act. This session covers what's actually required now.

• What APRA and ASIC's supervisory letters require.
• How voluntary standards under the National AI Plan are likely to harden.
• Building a governance framework that can flex as rules change.

AI is changing the speed and scale of cybercrime. Threat actors are using generative AI to create more convincing phishing campaigns, develop malicious code, automate attacks, and identify vulnerabilities faster than ever.

This panel will explore how AI is reshaping the threat landscape, what security teams are seeing in the real world, and whether defensive AI can keep pace with increasingly sophisticated attackers.

• How AI is accelerating attacks and shortening the time organisations have to respond.
• Real-world examples of AI-powered phishing, malware, and automated cyberattacks.
• Where defensive AI can keep pace with attackers and where human expertise is still essential.

Moving an AI model from pilot to production introduces new security challenges. Controls that worked during testing may not be enough once the model is handling real data, users, and business processes.

This case study explores how one team secured a live AI model without slowing down adoption or undermining the business value of AI.

• What security gaps emerged when the AI model moved from pilot to production.
• How the team approached access controls, logging, and continuous monitoring.
• The incident response playbook they developed to identify, contain, and respond to AI-related threats.

A hands-on, interactive session working through a real AI security and governance scenario as a room. Details announced soon.

As employees adopt AI tools faster than organisations can govern them, security teams are facing growing risks around sensitive data, third-party platforms, and unsanctioned AI use.

This case study explores how one organisation gained visibility over its AI usage and introduced a practical approach to managing risk without blocking innovation.

• How the organisation uncovered the scale of unsanctioned AI tools being used across the business.
• How they assessed and risk-tiered AI tools and vendors rather than introducing a blanket ban.
• How they created a clear pathway to approved AI tools that employees would actually use.

As AI agents gain greater autonomy and access to business systems, prompt injection and unexpected agent behaviour can create serious security risks.

This case study examines a real prompt injection incident involving a production AI agent, how the attack unfolded, and the security measures introduced to reduce the risk of it happening again.

• How the prompt injection attack worked and where existing security controls failed.
• Why prompt injection remains difficult to prevent with a single, permanent solution.
• How guardrails, sandboxing, and human oversight were introduced to make AI agents safer.

As AI becomes embedded in critical business systems, attackers are finding new ways to target the models and data behind them. From manipulating training data to creating convincing deepfakes, these threats are creating a new set of challenges for security teams.

This panel explores how these attacks work, what organisations are seeing in practice, and the steps security teams can take to strengthen AI systems without needing specialist research capabilities.

• How adversarial attacks and model poisoning work, and how they differ from prompt injection.
• How organisations are detecting and responding to deepfakes in real-world environments.
• Practical ways to strengthen AI models and data against emerging attacks.

Small-group, discussion-based sessions where you'll work through real AI security and governance challenges with peers in similar roles. Roundtable topics will be announced soon.

Put your knowledge to the test in this fast-paced quiz covering real-world trivia, key concepts, and emerging trends. Compete for bragging rights — and a voucher — as the top scorer takes the crown.

As AI agents become more common across the business, they can quietly gain access to sensitive systems, data, and applications without the same oversight as human users.

This case study explores how one organisation identified the access its AI agents had accumulated and introduced stronger governance to manage non-human identities and reduce security risk.

• How the organisation discovered what systems and data its AI agents could access.
• How they applied least-privilege principles to autonomous, non-human identities.
• How they built ongoing visibility and controls as new AI agents were introduced.

As AI becomes more widely used across organisations, boards are under growing pressure to understand and oversee the risks that come with it. The challenge is giving leaders the right level of insight without overwhelming them with technical detail.

This keynote explores how organisations can communicate AI risk clearly, establish accountability, and give boards the knowledge they need to make informed decisions.

• What effective AI risk reporting looks like at board and executive level.
• How to establish clear ownership and accountability for AI-related risks.
• How to build AI literacy at board level without getting lost in technical detail.

Where are organisations most exposed when it comes to AI? This interactive think tank will use live audience voting to uncover the biggest AI security and governance challenges organisations are facing today.

Compare your organisation's approach with peers, identify common gaps, and explore where security teams should be focusing their attention and investment.

1. What is your biggest AI security blind spot: shadow AI, agentic access, model attacks, or third-party tools?
2. Who is responsible for AI risk in your organisation?
3. Have you experienced a prompt injection or AI agent incident, even a near-miss?
4. Is your board asking the right questions about AI risk?
5. Where should your next AI security investment be focused?

Unwind with your peers for a couple of drinks on us!